Where to start?

Of all logistics SNAFUs, this is the hardest to explain.

The proof? Take a controlled subset, switch re-forecasting off, and see if it performs better or worse.

Someone who did halved their in-store stockouts. That's just short of a 10% increase in ex-stock service level.
Who wouldn't give their right eye for that?

Why such a 'ballsy' approach?

Words don't work. Or, if they do, they convince the head but not the heart.The Tools all use gameplay, and that really works well
(Call for a demo).

Meantime, for those who want words, try these.

Whether a customer buys or doesn't buy a particular SKU on a particular day is essentially a 'lightning strike'.
Across vast swathes of retail the average SKU only sells 1 per shop every 2 or 3 weeks.
To reforecast (and perhaps change the target stock) too often is to infer that the strikes are now - predictably - closer together,
or further apart, than they were.

If we could predict such chance events, we'd all be rich and the casinos poor.

Neither being true don't do it. It's that simple.

I suspect there's one other factor at play. Firms spend time and money implementing forecasting systems.
To switch them off, even if it's only an slow movers or only some of the time, would be to admit failure.

Tony Lines, who had some terrific tools in 'SlimStock', used to lament "If only I could teach people when not to forecast!"

We've sometimes viewed forecasting as an end in itself. It's not. It's a means to better whole chain performance.
That's if we even thought about it. More often, I suspect, we forecast 'because it ought to work'[1],
not because it does.
Indeed most firms I talk to have never tested if their forecasts make things better or worse.

An apocryphal economist was shown a prosperous nation with low inflation, good health, terrific state education and no crime.
He pondered "Ah!; but does it work in theory?"More recently "The problem with Wikipedia is that it only works in practice.
In theory, it can't possibly work." (From slashdot sig)